Although mouse allergen and pollutant exposures have been linked to asthma morbidity in poor minority populations, these factors do not account for most of the observed morbidity, so that additional environmental factors almost certainly contribute to asthma morbidity in this population. One intriguing environmental factor is diet since the population that is most affected by asthma morbidity and mortalitypoor, predominantly African American populations- have a Western style diet that is low in anti-oxidant foods and high in saturated fats. The ASTHMA-DIET Program's overall hypothesis is that a low antioxidant, pro-inflammatory diet impairs the capacity to respond to oxidative stressors, thereby increasing susceptibility to pollutant and mouse allergen exposure. The Data Management and Statistics Core (DMSC) will support the conduct of Projects 1, 2, and 3 of the ASTHMA-DIET Program. Specifically, the DMSC will develop recruitment and study subject tracking tools, data collection tools, and data management systems for the projects. The support services include data quality control/quality assurance, development of randomization schemes, and environmental and biologic specimen tracking. The DMSC will also conduct statistical analyses - from exploratory and interim analyses to final complex multivariate modeling under the direction of the senior biostatistician and Core Co-Leader. The DMSC also supports generation of abstracts and manuscripts. To facilitate interactions between the Environmental Assessment Core and the Projects, the DMSC manages a web-based data portal to facilitate quality control and transfer of environmental assay data to the DMSC. These activities to facilitate interactions will be expanded to include a bar-coding based sample tracking system that will be integrated with Project 3, which will support the conduct of the biomarker assays for Projects 1 and 2. The DMSC holds weekly Center-wide Data Management meetings to review current issues pertaining to any of its support activities. The DMSC serves a key support role, managing a very large amount of complex data which spans the spectrum from questionnaire data, clinical data, environmental exposure data, and biomarker data. The data management system serves to ensure integration of all Projects.